Gradient surgery for multi-task learning

Author: hkds

August undefined, 2024

WebJan 19, 2024 · We propose a form of gradient surgery that projects a task's gradient onto the normal plane of the gradient of any other task that has a conflicting gradient. On a series of challenging multi-task supervised and multi-task RL problems, this approach leads to substantial gains in efficiency and performance. WebJan 5, 2024 · The objective of multi-task learning (MTL) [ 3, 26] is to develop methods that can tackle a large variety of tasks within a single model. MTL has multiple practical benefits. First, learning shared parameters across multiple tasks leads to representations that can be more data-efficient to train and also generalize better to unseen data.

Gradient Surgery for Multi-Task Learning DeepAI

WebWe propose a form of gradient surgery that projects a task's gradient onto the normal plane of the gradient of any other task that has a conflicting gradient. On a series of … WebMDL-NAS: A Joint Multi-domain Learning framework for Vision Transformer Shiguang Wang · TAO XIE · Jian Cheng · Xingcheng ZHANG · Haijun Liu Independent Component Alignment for Multi-Task Learning Dmitry Senushkin · Nikolay Patakin · Arsenii Kuznetsov · Anton Konushin Revisiting Prototypical Network for Cross Domain Few-Shot Learning ioannis theofilakis

Gradient Surgery for Multi-Task Learning OpenReview

WebAbstract: Multi-task learning technique is widely utilized in machine learning modeling where commonalities and differences across multiple tasks are exploited. However, multiple conflicting objectives often occur in multi-task learning. ... Moreover, the gradient surgery for the multi-gradient descent algorithm is proposed to obtain a stable ... WebJan 19, 2024 · We propose a form of gradient surgery that projects a task's gradient onto the normal plane of the gradient of any other task that has a conflicting gradient. WebWe propose a form of gradient surgery that projects a task's gradient onto the normal plane of the gradient of any other task that has a gradient. On a series of challenging … on set death

Knowledge Distillation for Multi-task Learning SpringerLink

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WebGradient Surgery for Multi-Task Learning. In Proceedings of the 31st International Conference on Neural Information Processing Systems (Virtual Conference). Google Scholar; Zhe Zhao, Lichan Hong, Li Wei, Jilin Chen, Aniruddh Nath, Shawn Andrews, Aditee Kumthekar, Maheswaran Sathiamoorthy, Xinyang Yi, and Ed Chi. 2024. Recommending … WebNIPS ioannis toskas orthopädeWebWe identify a set of three conditions of the multi-task optimization landscape that cause detrimental gradient interference, and develop a simple yet general approach, projecting conflicting gradients (PCGrad), … onsetedittext

"WebGradient Surgery for Multi-Task Learning Figure 2: Conﬂicting gradients and PCGrad. In (a), tasks iand j have conﬂicting gradient directions, which can lead to destructive … " - Gradient surgery for multi-task learning

Gradient surgery for multi-task learning

WebWe propose a form of gradient surgery that projects a task's gradient onto the normal plane of the gradient of any other task that has a conflicting gradient. On a series of … WebSep 22, 2024 · Recent research has proposed a series of specialized optimization algorithms for deep multi-task models. It is often claimed that these multi-task optimization (MTO) methods yield solutions...

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WebSep 16, 2024 · Gradient surgery for multi-task learning. Advances in Neural Information Processing Systems, 33, 2024. A survey on multi-task learning. Jan 2024; Yu Zhang; Qiang Yang; Yu Zhang and Qiang Yang. A ... WebSummary and Contributions: This paper proposed projecting conflicting gradients (PCGrad) to solve the problem of conflicting gradient in multitask learning. Experiments on computer vision tasks and reinforcement learning tasks verifies the effectiveness of …

WebDec 6, 2024 · We propose a form of gradient surgery that projects a task's gradient onto the normal plane of the gradient of any other task that has a conflicting gradient. On a … WebGradient Surgery for Multi-Task Learning. While deep learning and deep reinforcement learning (RL) systems have demonstrated impressive results in domains such as image …

http://arxiv-export3.library.cornell.edu/pdf/2001.06782v1 Webdevise novel gradient agreement strategies based on gradi-ent surgery to alleviate their effect. The gradient surgery framework was introduced in [36] to address multi-task learning, and is rooted in a simple and intuitive idea. In general, deep neural networks are trained using gradient descent, where gradients guide the optimiza-

Web论文阅读：Gradient Surgery for Multi-Task Learning. Zhihao. ... 我们提出了一种梯度手术（Gradient Surgery）的形式，将任务的梯度投影到具有冲突梯度的任何其他任务的梯度的法线平面上。在一系列具有挑战性的多任务监督和多任务 RL 问题上，这种方法在效率和性 …

WebMulti-task learning has emerged as a promising approach for sharing structure across multiple tasks to enable more efﬁcient learning. However, the multi-task setting presents a number of optimiza- ... Figure 1: Visualization of gradient surgery’s effect on a 2D multi-task optimization problem. (a) A multi-task objective landscape. (b) & (c ... onset depression meaningWebSummary and Contributions: The paper proposes a gradient-based method for tackling multi-task learning problem, in which "conflicting" gradients are detected and altered so … ioannis thermal camera ioannis toumazou vs christopher payneWebSep 24, 2024 · Motivated by the insight that gradient interference causes optimization challenges, we develop a simple and general approach for avoiding interference … ioannis tournasWebPCGrad. This repository contains code for Gradient Surgery for Multi-Task Learning in TensorFlow v1.0+ (PyTorch implementation forthcoming). PCGrad is a form of gradient … ioannis tosounidisWebGradient Surgery for Multi-Task Learning gradient magnitudes. As an illustrative example, consider the 2D optimization landscapes of two task objectives in Figure1a-c.The opti-mization landscape of each task consists of a deep valley, a property that has been observed in neural network optimiza-tion landscapes (Goodfellow et al.,2014), and the ... ioannis toumazouWeb我们提出了一种梯度手术（Gradient Surgery）的形式，将任务的梯度投影到具有冲突梯度的任何其他任务的梯度的法线平面上。在一系列具有挑战性的多任务监督和多任务 RL 问 … on set editor